Chapter

Nonparametric models

Timo Teräsvirta, Dag Tjøstheim and W. J. Granger

in Modelling Nonlinear Economic Time Series

Published in print December 2010 | ISBN: 9780199587148
Published online May 2011 | e-ISBN: 9780191595387 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780199587148.003.0010

Series: Advanced Texts in Econometrics

Nonparametric models

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A difficulty of nonparametric techniques is the curse of dimensionality. One cannot estimate nonparametrically in high dimensions unless restrictions are made. The present chapter considers a selection of such more restrictive models. The techniques are intermediate between purely parametric and purely nonparametric. Prime among these models are additive models and the closely related functional coefficient models. The nonparametric structure is then typically allowed to depend on just one or two variables at a time. There is also the possibility of letting a nonparametric term depend on a linear combination of variables as in the index models or in projection pursuit. Finally, there are semiparametric models, where some of the variables are modelled parametrically, some nonparametrically.

Keywords: additive models; backfitting; functional coefficient model; index model; projection pursuit

Chapter.  12432 words.  Illustrated.

Subjects: Econometrics and Mathematical Economics

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